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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Sr. Technical Coach, IT - **Company:** Inspyr Solutions - **Location:** Fort Worth, TX, United States - **Experience:** Expert - **Salary:** $114,400.0 - **Contract:** Permanent contract - **Skills:** LangGraph Framework, Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Automation of Tests, Microsoft Azure, C Sharp (Programming Language), Cloud Computing, Code Generation, Profiling, Continuous Integration, Data Security, Software Debugging, DevOps, Distributed Systems, Github, Python (Programming Language), Object-Oriented Software Development, Scrum Methodology, Cloud Services, Elearning, Service-Oriented Architecture, Software Engineering, TypeScript, Test-Driven Development (TDD), ReactJS, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Concurrency, Spring-boot, Model Validation, Generative AI, AI Coding Agents, Agentic-AI, Fastapi, AngularJS, Kubernetes, Information Technology, Extreme Programming, AutoGen, Restful APIs, Pyramid, Semantic Kernel, Software Version Control, Human in the Loop, Docker - **Published:** October 29, 2026 - **Apply:** https://www.careerbuilder.com/job-details/sr-technical-coach-it-fort-worth-tx--3c3ccf93-dccb-4f30-9207-8a5daf18000e ## About the Role * Bachelor's degree in Computer Science or a related field, or equivalent education and professional experience. * 6+ years of relevant experience working in an Agile software engineering environment. * 5+ years of experience creating and delivering technical training. * Hands-on experience with software engineering, TDD, CI/CD, and Agile methodologies such as Scrum, Kanban, or Extreme Programming. * Experience using generative AI and AI coding assistants within software development or DevOps workflows. * Practical experience building or supporting AI agents and tool-enabled LLM workflows. * Strong understanding of responsible AI, secure data handling, AI-generated code risks, agent orchestration, tool calling, structured outputs, context management, and human-in-the-loop controls. * Experience testing nondeterministic systems and troubleshooting AI or agent-related failures. * Strong communication, facilitation, and coaching skills with the ability to simplify complex technical concepts. * Experience with modern development technologies such as Java, Python, C#, JavaScript, TypeScript, Spring Boot, FastAPI, Angular, React, Docker, Kubernetes, GitHub, Azure DevOps, AWS, Azure, REST APIs, and automated testing tools., * Experience developing labs and learning content for AI-assisted software engineering. * Familiarity with RAG, embeddings, vector databases, grounding, LLM APIs, model evaluation, and AI governance. * Experience integrating AI and agents with applications, APIs, CI/CD pipelines, cloud services, observability platforms, and enterprise knowledge sources. * Experience with agent frameworks such as Semantic Kernel, AutoGen, LangGraph, or similar technologies. * Familiarity with MCP, agent-to-agent communication, and multi-agent orchestration. * Knowledge of agent security concepts including prompt-injection defenses, permission boundaries, data-loss prevention, sandboxing, and audit trails. * Experience building CI/CD pipelines and applying the Testing Pyramid. * Experience with concurrency, debugging, performance profiling, optimization, resiliency, and distributed systems. ## Description We are looking for a Sr. Technical Coach to design and deliver engaging, hands-on technical learning experiences for software engineering teams. This role combines deep software engineering knowledge, Agile and DevOps expertise, and strong facilitation skills. The ideal candidate will be able to coach learners across modern engineering practices while also teaching the responsible and practical use of generative AI and agentic AI throughout the software development lifecycle., * Deliver instructor-led, hands-on training in software engineering, Agile, DevOps, cloud, CI/CD, testing, system design, and AI-assisted development. * Translate complex technical concepts into practical, easy-to-understand instruction for learners at different skill levels. * Teach responsible AI practices including privacy, security, bias awareness, output validation, and human oversight. * Coach learners on agentic AI concepts such as planning, tool use, memory, orchestration, multi-agent workflows, and human approval controls. * Develop and maintain technical curricula, labs, code samples, assessments, diagrams, and digital learning content. * Facilitate coding exercises, demonstrations, simulations, and collaborative problem-solving sessions. * Teach object-oriented design, service-oriented architecture, TDD, automated testing, the Testing Pyramid, source control, containers, Kubernetes, cloud platforms, and CI/CD practices. * Coach learners on debugging, concurrency, performance, resiliency, reliability, and maintainability. * Adapt learning content to distributed systems, high-volume applications, and enterprise use cases. * Track learner progress, assessments, learning paths, and training outcomes. * Partner with engineering leaders and subject matter experts to keep training content current and relevant. * Continuously improve learning programs based on learner performance, feedback, and business needs.